Yue Gao

An improved collaborative filtering recommendation algorithm not based on item rating

2015

As e-commerce grows fast nowadays, recommender systems have become an integral part of every electricity business. A number of the recommendation algorithms need score matrix (i.e., matrix that is used to record the data of …

Automatic Modulation Classification of Overlapped Sources Using Multi-Gene Genetic Programming With Structural Risk Minimization Principle

2018 · IEEE Access

As the spectrum environment becomes increasingly crowded and complicated, primary users may be interfered by secondary users and other illegal users. Automatic modulation classification (AMC) of a single source cannot recognize the overlapped sources. Consequently, …

Aligning Pretraining for Detection via Object-Level Contrastive Learning

2021 · arXiv (Cornell University)

Image-level contrastive representation learning has proven to be highly effective as a generic model for transfer learning. Such generality for transfer learning, however, sacrifices specificity if we are interested in a certain downstream task. We …

On the Limitations of Stochastic Pre-processing Defenses

2022 · arXiv (Cornell University)

Defending against adversarial examples remains an open problem. A common belief is that randomness at inference increases the cost of finding adversarial inputs. An example of such a defense is to apply a random transformation …

Generating Hypergraph-Based High-Order Representations of Whole-Slide Histopathological Images for Survival Prediction

2022 · IEEE Transactions on Pattern Analysis and Machine Intelligence

Patient survival prediction based on gigapixel whole-slide histopathological images (WSIs) has become increasingly prevalent in recent years. A key challenge of this task is achieving an informative survival-specific global representation from those WSIs with highly …

SEA: Shareable and Explainable Attribution for Query-based Black-box Attacks

2023 · arXiv (Cornell University)

Machine Learning (ML) systems are vulnerable to adversarial examples, particularly those from query-based black-box attacks. Despite various efforts to detect and prevent such attacks, ML systems are still at risk, demanding a more comprehensive approach …

Efficient Parallel Split Learning Over Resource-Constrained Wireless Edge Networks

2024 · IEEE Transactions on Mobile Computing

The increasingly deeper neural networks hinder the democratization of privacy-enhancing distributed learning, such as federated learning (FL), to resource-constrained devices. To overcome this challenge, in this paper, we advocate the integration of edge computing paradigm …

HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems

2025 · arXiv (Cornell University)

Split federated learning (SFL) has emerged as a promising paradigm to democratize machine learning (ML) on edge devices by enabling layer-wise model partitioning. However, existing SFL approaches suffer significantly from the straggler effect due to …

Hypergraph Foundation Model

2025 · IEEE Transactions on Pattern Analysis and Machine Intelligence

Hypergraph neural networks (HGNNs) effectively model complex high-order relationships in domains like protein interactions and social networks by connecting multiple vertices through hyperedges, enhancing modeling capabilities, and reducing information loss. Developing foundation models for hypergraphs …